This book is divided into two parts. In the first part we give an elementary introduction to computational physics consisting of 21 simulations which originated from a formal course of lectures and laboratory simulations delivered since 2010 to physics students at Annaba University.
Quantum computing by simulations is based upon similarity between mathematical formalism of quantum mechanics and phenomena to be computed. It exploits a dynamical convergence of several competing phenomena to an attractor which can represent an extrenum of a function, an image, a solution to a system of ODE, or a stochastic process.
Welcome to my collection titled Object-Oriented Programming (OOP) with Java. During the past eighteen years, I have published hundreds of Java and OOP programming tutorials on a variety of diferent topics and websites. I have also developed the teaching materials for several diferent college-level programming courses in Java/OOP.
In the year 2013, everything from parking meters to cell phones to Mars landing vehicles are controlled by computer code. That code is written by humans.
This book was written for an experimental freshman course at the University of Colorado. The course is now an elective that the majority of our electrical and computer engineering students take in the second semester of their freshman year, just before their first circuits course. Our department decided to order this course for several reasons:
The performance of dynamic object-oriented programming languages such as JavaScript depends heavily on highly optimizing just-in-time compilers.
Ruby is an object-oriented scripting language developed by Yukihiro Matsumoto ("Matz"). The main web site for Ruby is ruby-lang.org.
Most popular programming languages support situations where a value of one type is converted into a value of another type without any explicit cast. Such implicit type conversions, or type coercions, are a highly controversial language feature.
This book began as graduate class notes to supplement technical readings from anumber ofdisciplines. Over the years as I have worked on various projects, I kept running against the question, "What can I read to better understand this?"
In recent years, a growing number of organizations have been allocating vast amount of resources to construct and maintain databases and data warehouses. In scientific endeavours, data refers to carefully collected observations about some phenomenonunder study. In business, data capture information about economic trends, critical markets, competitors and customers. In manufacturing, data record machinery performances and production rates in different conditions. There are essentially two reasons why people gather increasing volumes of data: first, they think some valuable assets are implicitly coded within them, and computer technology enables effective data storage at reduced costs.
This module is one in a series of modules designed to teach you about the essence of Object-Oriented Programming (OOP) using Java with particular emphasis on accessibility for blind students.
The C programming language was created by Thompson and Ritchie around 1970 as the implementation language of the Unix operating system.
Here are some of my notes in English for beginners about reverse engineering who would like to learn to understand x86 (which accounts for almost all executable software in the world) and ARM code created by C/C++ compilers.
The traditional lecture has been a standard teaching tool for university courses all around the world. However, students have different methods of learning, and for those who learn best through visual means, lectures are often not enough to understand the concepts. This is a particular problem in computer science, because a strong grasp of the fundamentals is vital to a student’s understanding of the complexities of programming and computing in general.
Computers are awesome. The human race has seen more advancements in the last 50 years than in the entire 10,000 years of human history. Technology has transformed the way we live our daily lives, how we interact with each other, and has changed the course of our history. Today, everyone carries smart phones which have more computational power than supercomputers from 20 years ago. Computing has become ubiquitous, the “internet of things” will soon become a reality in which every device will become interconnected and data will be collected and available even about the smallest of minutiae.
Why mathematics in a book about algorithmics? Algorithms are, in essence, applied mathematics. Even if they deal with apparently “unmathematical” subjects such as manipulating strings or searching objects, mathematics is the basis. To mention just a few examples: the classical algorithmic concept of recursion is very closely related to the principle of mathematical induction; rigorous proofs are needed for establishing the correctness of given algorithms; running times have to be computed.
Although C# is derived from the C programming language, it has features such as garbage collection that allow beginners to become proficient in C# more quickly than in C or C++.
There’s something rather unique in Erlang in how it approaches failure compared to most other programming languages. There’s this common way of thinking where the language, programming environment, and methodology do everything possible to prevent errors. Something going wrong at run-time is something that needs to be prevented, and if it cannot be prevented, then it’s out of scope for whatever solution people have been thinking about.
This book has emerged from my lecture notes for an introductory course in compiler design at ETH Zürich. Several times I have been asked to justify this course, since compiler design is considered a somewhat esoteric subject, practised only in a few highly specialized software houses. Because nowadays everything which does not yield immediate profits has to be justified, I shall try to explain why I consider this subject as important and relevant to computer science students in general.
Coding standards and good practices are fundamental to a disciplined approach to software projects, whatever programming languages they employ. Prolog programming can benefit from such an approach, perhaps more than programming in other languages. Despite this, no widely accepted standards and practices seem to have emerged up to now.
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